30 citations · 38 across the 7 of their papers we have counts for
8 papers
Beyond the shortest path: the path length index as a distribution
Leonardo B. L. Santos, Luiz Max Carvalho, Giovanni G. Soares +2
The traditional complex network approach considers only the shortest paths from one node to another, not taking into account several other possible paths. This limitation is signif…
Precipitation event-based networks: an analysis of the relations between network metrics and meteorological properties
Aurelienne A. S. Jorge, Douglas Uba, Alex A. Fernandes +2
The study of complex systems in nature is essential to understand the interactions between different elements and how they influence one another. Complex network theory is a powerf…
Flood risk map from hydrological and mobility data: a case study in São Paulo (Brazil)
Lívia Rodrigues Tomás, Giovanni Guarnieri Soares, Aurelienne A. S. Jorge +3
Cities increasingly face flood risk primarily due to extensive changes of the natural land cover to built-up areas with impervious surfaces. In urban areas, flood impacts come main…
Global-threshold and backbone high-resolution weather radar networks are significantly complementary in a watershed
Aurelienne A. S. Jorge, Iuri da Silva Diniz, Vander L. S. Freitas +2
There are several criteria for building up networks from time series related to different points in geographical space. The most used criterion is the Global-Threshold (GT). Using…
Vulnerability analysis in Complex Networks under a Flood Risk Reduction point of view
Leonardo B. L. Santos, Giovanni G. Soares, Tanishq Garg +7
The measurement and mapping of transportation network vulnerability to natural hazards constitute subjects of global interest, especially due to climate change, and for a sustainab…
(geo)graphs - Complex Networks as a shapefile of nodes and a shapefile of edges for different applications
Leonardo B L Santos, Aurelienne A S Jorge, Marcio Rossato +4
Spatial dependency and spatial embedding are basic physical properties of many phenomena modeled by networks. The most indicated computational environment to deal with spatial info…